Sr. AI Engineering Lead

Introduction

Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together.

Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.

The Senior AI Engineering Lead owns the technical delivery of enterprise AI solutions at AJ Gallagher. Reporting to the Director of AI, you will lead the design, build, and deployment of production AI systems - RAG pipelines, agentic workflows, and Copilot integrations - on our Azure and .NET/Python stack. You will set engineering standards for a growing AI team, mentor developers, and partner directly with business units to turn ambiguous problems into shipped, governed, production-grade AI products in a regulated insurance environment.

• Translate Business Problems into Technical Solutions: Work side-by-side with business leaders and subject-matter experts to unpack ambiguous, unstructured challenges and shape them into well-scoped, buildable AI solutions with a clear delivery path.
• Own AI Solution Architecture: Design and defend end-to-end architectures for GenAI and agentic systems on Microsoft Foundry - spanning Azure OpenAI, Azure AI Search, Foundry Tools, and Copilot Studio - that meet enterprise security, scalability, and data‑residency requirements.
• Lead Hands-On Delivery: Write and review production code (C#/.NET and Python) for RAG pipelines, AI agent orchestration, and API integrations; remain a strong individual contributor while leading the team.
• Set Engineering Standards: Establish patterns for agentic development, evaluation, testing, CI/CD (Azure Dev Ops), and observability so AI solutions are repeatable and maintainable - not one-off prototypes.
• Mentor and Grow Engineers: Coach AI developers through design reviews, pairing, and career development; raise the technical bar across the team.
• Ship to Enterprise Surfaces: Deliver AI capabilities into internal applications, Microsoft Teams, and M365 Copilot, integrating through Foundry agents, Service Bus, Azure Functions, and other cloud-native services.
• Build Governance In: Implement responsible‑AI controls - Entra /RBAC, IaC Policy, human‑in‑the-loop checkpoints, audit logging - aligned to Gallagher compliance expectations from day one, not as an afterthought.
• Drive Evaluation and Reliability: Define measurable quality bars (groundedness, accuracy, latency, cost) and build the evaluation harnesses to enforce them before and after release.
• Communicate Up and Across: Translate technical trade-offs into clear recommendations for the Director of AI and business stakeholders; manage delivery risks and dependencies proactively.

• Experience: 7 or more years in software engineering, including experience in building LLM/GenAI systems in production and 2+ years leading engineers or owning technical direction.
• Azure Depth: Hands‑on production experience with Microsoft Foundry, Azure OpenAI Service, Azure AI Search, and Azure compute (Functions, Container Apps, or App Service).
• Languages: Strong .NET/C# plus working proficiency in Python; able to review and contribute in both.
• GenAI Engineering: Proven delivery of RAG architectures, agent orchestration (Microsoft Agent Framework, Semantic Kernel, or Lang Chain), and prompt/evaluation pipelines.
• API and Integration
  
  Skills:
  
  Designing secure REST APIs and event‑driven integrations (Azure API Management, Service Bus) within an enterprise identity model (Entra , RBAC).
• Delivery Discipline: Agile experience with Azure Dev Ops (or equivalent) -…